1. Field of the Invention
The present invention relates to a video system conversion method, and more particularly, to a video system conversion method for converting an interlaced image into a progressive image by applying an interpolation algorithm.
2. Description of the Related Art
In the major video format of the conventional technique, the video frame is divided into an odd filed and an even filed, wherein the image scanning lines interleaved with each other are included therein. The odd field and the even field are independently scanned with a scanning period of every 1/60 second and both fields are interleaved with each other to form a frame. Referring to FIG. 1, the position PO of an object in an odd field (i.e. the 1st field of FIG. 1) on the kth scanning line is scanned at a specific time point. After a scanning period is passed, the same object is corresponded to the position PE of an even field (i.e. the 2nd field of FIG. 1). However, meanwhile the scanning lines only include the (k−1)th scanning line and the (k+1)th scanning line, but the kth scanning line is not included. Therefore, if it is to represent a pixel corresponding to the odd field on the even field, e.g. a pixel on the position PE of the kth scanning line, an estimation value is obtained by applying a specific interpolation algorithm with referring to the pixel values on the even field such as the (k−1)th scanning line and the (k+1)th scanning line, such that the interlaced image is converted to the progressive image. Such method is also known as the deinterlacing method, which is an important digital video technique. In order to eliminate the inter-field flickering due to the motion gap, a conventional technique performing an inter-field interpolation for data on the edge of a motion object in image is roughly described hereinafter.
The conventional method performs an interpolation operation on the pixel value of a set of neighboring pixels, so as to estimate a pixel value of a target pixel on the scanning lines in another field. The interpolation algorithm is especially effective for estimating the pixel value in a filed when detecting the data having edges in image. As shown in FIG. 2, in the conventional algorithm, it is to obtain the corresponding difference values of the pixel values Qa−3, Qa−2, Qa−1, Qa, Qa+1, Qa+2, Qa+3 and Qb−3, Qb−2, Qb−1, Qb, Qb+1, Qb+2, Pb+3, respectively, which are the pixel values of two sets of pixels on the scanning lines 200 and 202 above/below the target pixel (its value is T) on the edge or most close to the edge. Then, a pixel mean of the set of pixels having the minimum difference value is used as a target pixel value, namely the pixel value T on the interpolation line 204. In other words, it is to obtain the minimum value of |Qa−3−Qb+3|, |Qa−2−Qb+2|, |Qa−1−Qb+1|, |Qa−Qb|, Qa+1−Qb−1|, |Qa+2−Qb−2|, |Qa+3−Qb−3|, and further to obtain a mean (Qx+Qy)/2 of a set (Qx, Qy), in which the minimum value is located on, as the T value. The shortcoming of such interpolation algorithm is if the variance of the reference pixel value neighboring to the target pixel is too big and is corresponded to a set having the minimum value, the mean is departed from the pixel value too far, wherein the mean makes the edge 20 of the image more smoothly. For example, it is assumed that the pixel values of Qa and Qb are 100, 101 respectively, and both the pixel values of Qa+3 and Qb−3 are 150, since the difference value is 0 and its value is less than all other sets, the minimum difference value is corresponded to (Qa+3, Qb−3) set. Accordingly, T value is assigned as (150+150)/2=150 rather than the pixel value of Qa or Qb that is closer in practical.
In order to eliminate the shortcoming of the conventional technique mentioned above, the present invention discloses an improved interpolation algorithm for avoiding the abnormal departure of the pixel value of the target pixel due to the special case mentioned above.